Metadata-Version: 2.1
Name: fast-curator
Version: 0.1.4
Summary: F.A.S.T. package for describing datasets
Home-page: https://gitlab.cern.ch/fast-hep/public/fast-curator
Author: F.A.S.T
Author-email: fast-hep@cern.ch
License: Apache Software License 2.0
Description: [![pypi package](https://img.shields.io/pypi/v/fast-curator.svg)](https://pypi.org/project/fast-curator/)
        [![pipeline status](https://gitlab.cern.ch/fast-hep/public/fast-curator/badges/master/pipeline.svg)](https://gitlab.cern.ch/fast-hep/public/fast-curator/commits/master)
        [![coverage report](https://gitlab.cern.ch/fast-hep/public/fast-curator/badges/master/coverage.svg)](https://gitlab.cern.ch/fast-hep/public/fast-curator/commits/master)
        
        fast-curator
        =============
        Create, read and write dictionary descriptions of input datasets to process.
        Currently all datasets are expected to be built from sets of ROOT Trees.
        
        ## Requirements
        
        
        ## Installing
        ```
        pip install --user fast-curator
        ```
        
        ## Usage
        ```
        # Local files:
        fast_curator -o output_file_list.txt -t tree_name -d dataset_name --mc input/files/*root
        
        # Single XROOTD files:
        fast_curator -o output_file_list.txt --mc root://my.domain.with.files://input/files/one_file.root
        
        # XROOTD files with several globs
        fast_curator -o output_file_list.txt --mc root://my.domain.with.files://inp*/files/*.root
        ```
        
        Notes:
        1. If the command is called multiple times with the same output file (using the `-o` option), the additional files specified will be appended to the output file.
        2. Arbitrary meta-data (such as cross-section, data quality, generator precision, etc) can be added to each dataset with
           the `-m` option.
        
        For more guidance try the built-in help:
        ```
        fast_curator --help
        ```
        
        ## Reading dataset files back
        ```
        import fast_curator
        datasets = fast_curator.read.from_yaml("my_dataset_file.yml")
        ```
        Will return a list of datasets with the `default` section applied to each dataset.
        
        ## Further Documentation
        Is on its way...
        
Keywords: ROOT,analysis,particle physics,HEP,F.A.S.T
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
Provides-Extra: ROOT
